Create hash from string

Data Structures 101: implement hash tables in JavaScript

In computer programming, data structures are used to organize data and apply algorithms (or commands) to code. Having a good understanding of data structures and algorithms is useful for efficient problem-solving and essential to cracking coding interviews.

We will continue with our data structures series with one of the top data structures, the Hash Table. We’ll learn what they are, what they are used for, and how to implement them in JavaScript.

Today, we will cover:

What is a hash table?

A hash table (often called a hash map) is a data structure that maps keys to values. Hash tables combine lookup, insert, and delete operations in an efficient way. The key is sent to a hash function that performs arithmetic operations on it. The result (called the hash value or hash) is an index of the key-value pair.

Think of this like a signature on a block of data that allows us to search in constant time. A hash table operates like a dictionary that we can map to get from the hash to the desired data.

This data structure is widely used in many kinds of computer software, particularly for associative arrays, database indexing, caches, and sets. Usually, this operation returns the same hash for a given key.

The performance of a hash table depends on three fundamental factors: hash function, size of the hash table, and collision handling method.

Hash tables are made up of two parts:

• Object: An object with the table where the data is stored. The array holds all the key-value entries in the table. The size of the array should be set according to the amount of data expected.
• Hash function (or mapping function): This function determines the index of our key-value pair. It should be a one-way function and produce the a different hash for each key.

Note: In JavaScript, hash tables are generally implemented using arrays as they provide access to elements in constant time.

Uses of hash tables

Hash tables provide access to elements in constant time, so they are highly recommended for algorithms that prioritize search and data retrieval operations. Hashing is ideal for large amounts of data, as they take a constant amount of time to perform insertion, deletion, and search.

In terms of time complexity, the operation is 0 ( 1 ) 0(1) 0 ( 1 ) . On average, a hash table lookup is more efficient than other table lookup data structures. Some common uses of hash tables are:

• Database indexing
• Caches
• Unique data representation
• Lookup in an unsorted array
• Lookup in sorted array using binary search

Hash tables vs. trees

Hashing and trees perform similar jobs, but various factors in your program determine when to use one over the other.

Trees are more useful when an application needs to order data in a specific sequence. Hash tables are the smarter choice for randomly sorted data due to its key-value pair organization.

Hash tables can perform in constant time, while trees usually work in O ( l o g n ) O(log n) O ( l o g n ) . In the worst-case scenario, the performance of hash tables can be as low as O ( n ) O(n) O ( n ) . An AVL tree, however, would maintain O ( l o g n ) O(log n) O ( l o g n ) in the worst case.

An efficient hash table requires a hash function to distribute keys. A tree is simpler, since it accesses extra space only when needed and does not require a hash function.

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JavaScript hash()

Hash function in Javascript is any function that takes input as arbitrary size data and produces output as fixed-size data. Normally, the returned value of the hash function is called hash code, hash, or hash value. As already mentioned, hash returns the fixed size, which means that whatever size the input data is, a fixed size data will be received after processing the input data with a hash function. Let us look into more details on hash function in the following sections, such as syntax, working, examples, and advantages.

Web development, programming languages, Software testing & others

Below is the syntax of the hash function.

Here, the hash value will be returned if this function is called.

How does hash() Function Works in JavaScript?

In a Hash Table, a hash function will be used for computing the index into an array of slots or buckets, from which the preferred value can be identified. Suppose the following code has to be used for building.

The array of the same will be as shown below.

In order to get the right index of name, place and age, hash functions have to be called as shown below.

• For getting the index of name, hashfunc(“name”) will be called, and1 will be returned.
• For getting the index of place, hashfunc(“place”) will be called, and 2 will be returned.
• For getting the index of age, hashfunc(“age”) will be called, and 0 will be returned.

As there is no particular order in the array, the index of the array is merely bound to the key. Now, let us see the hash function constraints:

1. It Should be Deterministic

Suppose we input the same key; the same array index should be returned. Otherwise, the value won’t be found as the data doesn’t alter its position in the array.For example, let us consider const hash1 = (num) =>num % 9 which has the deterministic property. At the same time, const hash2 = (num) =>num % 9 + Math.random() won’t be used, as for different calls of hash2 will obtain different results for the same input. Moreover, these hash functions sometimes get an external parameter for hashing. Suppose, const hash3 = (num, param) =>num % param, hash3 will have deterministic property, as for the same data given as input and the similar parameters, the same output will be returned.

2. It Should Be Fast

The hash function has to be used every time we create, read, update, or delete data. Therefore, the hash function should be fast, and moreover, it should not be connected to the existing data length. That is, O(1).

3. It Should Be Uniform Distributed

Suppose there is an array of length 3. If 3 more places have to be added to an array with 2 positions to store data, 2 values have to be stored in 1 place. As this situation causes collision(two values place at one position), which leads to more computational work, uniform distribution has to be done for array indexes. For example, in the previous example, hash1(1) = hash1(10). It is important that for a good hash function, two different values for a and b should be considered (hash(a) = hash(b)). Algorithms such as brute force are available to identify such values for good hash functions. But, for several hash functions, on a normal group of supercomputers, millions of years has to be needed to find such values.

4. It Should Be Non-Invertible

The final important property of the hash function is the non-invertible property. It means, if a hash code is available, original data cannot be recovered without using a lot of resources for computing. Moreover, it cannot find original data. That is, if a hash code h is available, value x cannot be found, that hash(x) = h. Now, let us see how a hash function has to be created.

Create a function func and set the hash variable as 0. Then perform the coding as needed. Below is the sample hash function.

function func(string) < //set variable hash as 0 var hash = 0; // if the length of the string is 0, return 0 if (string.length == 0) return hash; for (i = 0 ;ireturn hash;

Example of JavaScript hash()

Let us see the sample program on the hash function in javascript.

Example #1

Javascript program to create a hash function that returns a hash code.

     h1 h3  
Sample output
 
Creation of hash from string
 
Hash value of the given string 'Happy moments' is :
    

First, create titles and headers. Once it is created, create a hash function that converts an integer to 32bits. In that function, the first set variable hash as 0. If the length of the string is 0, return 0. Otherwise, perform the code in for loop, which gives the input string as Happy moments. On executing the code, texts in headers that have colors and a hash value will be returned.

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Hashing in JavaScript

In hashing, all the operations like inserting, searching, and deleting can be performed in O(1) i.e. constant time. The worst case time complexity for hashing remains O(n) but the average case time complexity is O(1).

Basic Operations with Syntax:

HashTable: Used in order to create a new hash table.

// function to delete a key from the hashtable delete (key) < const index = this._setKey(key); if (this.table[index]) < this.table[index] = []; this.size--; return true; >else < return false; >>

Get: Used to search a key inside the hash table and return the value that is associated with that key.

// function inside hashtable class to // access a value using its key get(key)

Insert: Used to insert a new key-value pair inside the hash table.

// function to insert a value in the // hash table using setKey function insert(value)

Search: Used to search for a value.

// search a value (by getting its // key using setKey function) search(value)

Delete: Used in order to delete a particular key-value pair from the hash table.

// function to delete a key from the hashtable delete (key) < const index = this._setKey(key); if (this.table[index]) < this.table[index] = []; this.size--; return true; >else < return false; >>

Components of Hashing in Javascript:

1. Hash Table: A hash table is a generalization of the array. It gives the functionality in which a collection of data is stored in such a way that it is easy to find those items later if required. This makes searching for an element very efficient.

2. Hash Function: A hash function is used to transform a given key into a specific slot index. it is used to map each and every possible key into a unique slot index. If every key is mapped into a unique slot index, then the hash function is known as a perfect hash function. It is very difficult to create a perfect hash function but our job as a programmer is to create such a hash function with the help of which the number of collisions is as few as possible.

A good hash function should have the following properties:

• Efficiently computable.
• Should uniformly distribute the keys (Each table position is equally likely for each).
• Should minimize collisions.
• Should have a low load factor(the number of items in the table divided by the size of the table).

3. Collision Handling: Since a hash function gets us a small number for a big key, there is a possibility that two keys result in the same value. The situation where a newly inserted key maps to an already occupied slot in the hash table is called collision and must be handled using some collision handling technique. Following are the ways to handle collisions:

• Chaining: The idea is to make each cell of the hash table point to a linked list of records that have the same hash function value. Chaining is simple but requires additional memory outside the table.
• Open Addressing: In open addressing, all elements are stored in the hash table itself. Each table entry contains either a record or NIL. When searching for an element, we examine the table slots one by one until the desired element is found or it is clear that the element is not in the table.

Implementation with Example:

Step 1: Create a HashTable class with table and size initial properties.

Step 2: Add a private setKey(key) function to transform keys into indices.

Step 3: Add the insert() and get()functions for adding and accessing key-value pairs from the table.

Step 4: Add a remove() function to remove a key from the hash table.

Example 1: Suppose we have to store 5 numbers 100,87,86,12,25 and 9 in a hashtable. In this case, we will create a setKey function in which we will take the value as an argument and convert it to an index of the hash table. Below is the implementation.

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